Barclays is a UK bank ranked 20th on S&P Global’s list of the top 100 banks. Like other top banks, Barclays has forayed into AI for a variety of use-cases. The bank seems to work with AI vendors more than it builds AI applications in-house, which aligns with the general trend of AI adoption in financial services: 68% of the AI products we researched as part of our AI Opportunity Landscape research in financial services were bought from vendors.
Supply chains contain every material, component, product and packaging for the objects that together compose the world we live in. However, there is an often invisible ingredient to successful supply chains: data.
Consultants and professional services leaders face one of the hardest times in business in the last century.
Sales are drying up, companies are pulling back budgets, millions are jobless, and the business world scrambles to find some solid ground for a “new normal.”
For consultants whose livelihoods depend on closing deals, delivering value, and maintaining lucrative contracts, the economic conditions alone make things challenging.
But the economy is one of two great threats.
The second challenge for consultants doubles as an opportunity: Technology priorities are changing quickly.
At Emerj Artificial Intelligence Research, we’re fortunate to have a finger on the pulse of enterprise priorities in real time. Our research connections, our renowned AI podcast (closing in quickly on 3 million total downloads), and our enterprise client list allow us to gather intelligence fast. At no time has that been more important than during the coronavirus crisis.
Through polls of hundreds of enterprise leaders, in-depth interviews with directors of strategy and innovation at some of the world’s largest companies, and conversation with countless startup leaders, the new priority is clear:
It goes by many names: “Getting lean”, “streamlining operations”, and above all else - “automation.”
The era of Robotic Process Automation (RPA) and Artificial Intelligence (AI) will be ushered in by sheer necessity, and enterprises know it.
Consultants with experience in specific IT domains or traditional means of “digital transformation” will find clients with entirely new demands and questions, and the vast majority of consultants will lose out.
Our research has lead us to two requirements that the COVID-19 era consultant must have:
UBS is a Swiss multinational investment banking and financial services company ranked 30th on S&P Global’s list of the top 100 banks. In addition to investment banking and wealth management, the company is looking to improve its tech stack through several AI projects.
The insurance industry is being disrupted like it hasn't in decades. Unlike other events like Hurricane Sandy or even the 2008 financial crisis, the coronavirus is impacting essentially every corner of the world and more or less every industry.
Morgan Stanley is a US financial institution known mostly for its financial advisory services. According to our AI Opportunity Landscape research in financial services, approximately 10% of AI vendor products in the industry are wealth management solutions, and 4% are asset management solutions.
The financial sector was among the first to adopt artificial intelligence in business by automating fraud prevention with anomaly detection technology. Now financial institutions, including lenders, stand to benefit from automating back-end processes by digitizing documents and eliminating manual data entry.
In the last two articles in this 3-part series, we discussed how AI priorities will shift in response to the coronavirus pandemic, as well as how companies can further leverage the advantages they have (and can create) to overcome the challenges they are facing in this uncertain time.
At Emerj, our research involves tracking AI and innovation across industries, dialing into where AI is driving ROI, which we do through our AI Opportunity Landscape research. In these hard times, we're expecting many AI startups to fade away and many technology priorities within large enterprises to completely shift to be more in line with what we're going to be articulating in this article.
Progressive is one of the largest auto insurers in the US. The company has been experimenting with AI since the middle of the 2010s, with customer-facing applications that update insurance premiums based on driving habits and answer questions in a chat window. In this article, we discuss both of these AI use-cases. More specifically: